• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.275-289
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• 2021

Although the need for global citizenship education (GCE) has been emphasized globally, Korea lacks GCE for child welfare workers who affect children's global citizenship. In response, this study analyzed the reality of educational needs by (a) investigating domestic and international GCE policies, (b) doing the in-depth interviews with experts, and (c) surveying workers. According to the policy analysis, GCE in Korea has been mainly conducted through the school system but it was conducted in various ways worldwide. The need to expand GCE in Korea was also emphasized in the in-depth interview. The survey analysis showed that the path relationship among awareness-interest-desire to participate in GCE was significant, indicating that increasing awareness and interest for GCE was effective in real action. Based on this, we confirmed that GCE is a necessary education for child welfare workers, emphasized the need to raise awareness of GCE based on the AIDA model, and presented indicators that can be used for GCE.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.840-847
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• 2022

In a deep neural network (DNN)-based speech enhancement, using global and local input speech information is closely related to model performance. Recently, a nested U-Net structure that utilizes global and local input data information using multi-scale has bee n proposed. This nested U-Net was also applied to speech enhancement and showed outstanding performance. However, a single skip connection used in nested U-Nets must be modified for the nested structure. In this paper, we propose a multi-level skip connection (MLS) to optimize the performance of the nested U-Net-based speech enhancement algorithm. As a result, the proposed MLS showed excellent performance improvement in various objective evaluation metrics compared to the standard skip connection, which means th at the MLS can optimize the performance of the nested U-Net-based speech enhancement algorithm. In addition, the final proposed m odel showed superior performance compared to other DNN-based speech enhancement models.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.197-197
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• 2023

본 연구에서는 2018년부터 2021년까지의 국가가뭄정보통계집 자료를 바탕으로 호서 지역 내 농업가뭄 피해 사례들을 심층분석하고, 당시 지원된 농업용수 공급량에 주목하여 실제 용수 공급에 영향을 미친 잠재적 요인들의 특성을 파악하였다. 먼저, 농업가뭄 피해를 가뭄 당시 실제 공급된 농업용수량으로 정의하고, 피해 민감도라는 개념을 새롭게 도입하여 잠재적 영향 요인들과 농업용수 공급량 간의 지역별 연관성을 분석하였다. 본 연구는 농업 환경과 기상 조건 관련 인자들을 잠재적 영향 요인으로 규정하고, 연도별 도시면적당 농경지 면적 비율, 도시인구수 대비 농업종사자 비율, 전체 용수 이용량 대비 농업용수 비율, 월별 강수량, SPI(-3, -6, -9 및 -12)를 대상으로 연구를 수행하였다. 이러한 인자들의 변화에 따른 실제 공급된 농업용수량의 변화 정도를 수치화하여 지역별 피해 민감도를 산정하였다. 이를 위해, 먼저 잠재적 영향 요인과 실제 공급한 농업용수의 전월대비 증감량을 2018년부터 2021년까지 월별로 계산하였으며, 최대·최소 정규화를 통해 0부터 1 사이의 값으로 수치화하였다. 앞서 언급한 월별 증감량의 비율을 바탕으로 4년간의 절대적 수치 변화 정도를 비교·분석하였다. 그 결과, 농업 환경 관련 인자들 중 전체 용수 이용량 대비 농업용수 비율이 상대적으로 피해 민감도가 큰 것으로 나타났으며 기상 조건 관련 인자의 경우, SPI-9에 대한 피해 민감도가 가장 높은 수준임을 확인하였다. 추후, 본 연구에서 제안한 방법을 바탕으로 다양한 요인들에 대한 피해 민감도 산정 결과들이 도출된다면 농업가뭄 피해 시 농업용수 공급의 적절성 여부를 판단하는 데 있어 유용한 정보를 제공할 수 있을 것으로 사료된다.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.277-283
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• 2022

The purpose of this study is to study the user experience that provides psychological stability when paying for mobile e-commerce pay one-touch. Through literature and case studies, e-commerce pay one-touch payments were identified, and user experiences were investigated through surveys and in-depth interviews. The survey based on Aaron Walter's model of user needs received a high average of functionality and usability for one-touch payments, but reliability and stability were somewhat low. Afterwards, four design improvement plans were presented to supplement psychological stability by analyzing in-depth interviews conducted based on the User's Eye View of User Experience Design model. This study is expected to be helpful in basic research on the payment experience where you can feel stable when taking one-touch payments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.474-476
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• 2021

Glioblastoma is the most common brain malignancies arising from glial cells. Early diagnosis and treatment plan establishment are important, and cancer is diagnosed mainly through T1CE imaging through injection of a contrast agent. However, the risk of injection of gadolinium-based contrast agents is increasing recently. Region segmentation that marks cancer regions in medical images plays a key role in CAD systems, and deep neural network models for synthesizing new images are also being studied. In this study, we propose a model that simultaneously learns the generation of T1CE images and segmentation of cancer regions. The performance of the proposed model is evaluated using similarity measurements including mean square error and peak signal-to-noise ratio, and shows average result values of 21 and 39 dB.

• Industry Promotion Research
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• v.9 no.3
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• pp.175-183
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• 2024

The purpose of this study is to derive a UX that can help the use of fintech applications by senior users in their 60s or older, which has naturally increased with the increase in the elderly population. The study extracted five factors commonly considered important in fintech applications and was conducted based on a survey of general users and in-depth interviews with senior users. The research factors were extracted through a literature review into three general user experience research factors and two senior user experience research factors. After a survey targeting general users, in-depth interviews were conducted with senior users. As a result, we found notable differences in concerns about responsiveness and perceived usefulness between general and senior users. Based on the characteristics derived from the results of this study, we designed UX to help senior users use fintech applications.

• Journal of Korean Society of Water and Wastewater
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• v.38 no.3
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• pp.165-175
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• 2024

The dissolved air at the bottom layer of the deep aeration tank transforms into fine gas bubbles within the MLSS (Mixed Liquor Suspended Solid) floc when exposed to the atmosphere. MLSS floc flotation occurs when MLSS from the deep aeration tank enters the secondary clarifier for solid-liquid separation, as dissolved air becomes fine air within the MLSS floc. The floated MLSS floc causes a high SS (Suspended Solid) concentration in the secondary effluent. The fine air bubbles within the MLSS floc must be removed to achieve stable sedimentation in the secondary clarifier. Fine bubbles within the MLSS floc can be removed by air sparging. The settleability of MLSS was measured by sludge volume indexes (SVIs) after air sparging MLSS taken at the end of the deep aeration tank. MLSS settling tests were performed at MLSS heights of 200, 300, 400, and 500 mm, and compressed air was fed at the bottom of the settling column with air flow rates of 100, 300, and 500 ml/min at each MLSS height, respectively. Also, at each height and air flow rate, air was sparged for 3, 5, and 7 minutes, respectively. SVI was determined for each height, air flow rate, and sparging time, respectively. Experimental results showed that a 300 mm MLSS height, 300 ml/min air flow rate, and 3 minutes of sparging time were the least conditions to achieve less than 120 ml/g of SVI, which was the criterion for good MLSS settling in the secondary clarifier.

• Science of Emotion and Sensibility
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• v.26 no.1
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• pp.17-32
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• 2023

This study aims to study the impact of pet attachment on subjective well-being, focusing on individuals who live with pets. In addition, it is to recognize that their basic psychological requirement mediates between pet attachment and subjective well-being. For this purpose, a survey was performed on 358 adults living with pets nationwide. The final data of 319 people were evaluated after excluding invalid information. Dependent on the theoretical approach of the attachment theory, the human-pet relationship was examined by dividing it into two orthogonal dimensions pet attachment prevention and pet attachment anxiety(Zilcha-Mano et al., 2011). The mediating effects were investigated as an in-depth mechanism that mediates between pet attachment and subjective well-being, the mediating effects were examined, in terms of the three basic psychological needs of Self-Determination Theory, which are autonomy, competence, and relatedness. As an outcome, first, pet attachment prevention and pet attachment anxiety both revealed a negative correlation with subjective well-being. Second, basic psychological needs, which are autonomy, competence, and relatedness, are mediated between pet attachment and subjective well-being. Autonomy, competence, and relatedness fully mediated the relationship between pet attachment avoidance and subjective well-being. Meanwhile, in the case of pet attachment anxiety, only autonomy among basic psychological needs is fully mediated between pet attachment anxiety and subjective well-being in the case of pet attachment avoidance. This means that pet attachment prevention or pet attachment anxiety correlates with subjective well-being by satisfying basic psychological needs instead of directly affecting personal well-being. Regarding the pet effect, it is meaningful to find an in-depth mechanism that the human-pet relationship has for an adaptive and positive impact on humans.

• Journal of the Geological Society of Korea
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• v.54 no.5
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• pp.489-499
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• 2018

A series of geological events such as the formation of the Antarctic continental ice sheets, the changes in ocean circulation and a mass extinction after the onset of Oligocene has been studied as major concerns by various researches. However, paleoclimatic and paleoceanographic changes during the most period of Oligocene since the Eocene-Oligocene transition (EOT) still remains unclear. Especially, although the late Oligocene warming (LOW) has been assessed as the largest period in the paleoceanographic changes, the detailed understanding on the changed components is very low. The purpose of this study is the reconstruction of the paleoceanographic history during the late Oligocene using core sediments from IODP Expedition 342 Site U1406 performed in J-Anomaly Ridge in North Atlantic. Because North Atlantic deep water (NADW) has flowed southward through the study area since the early Oligocene, this area has been considered to an important location for studies on the changes of NADW. The core sediment analyzed in this study were deposited from about 26.0 to 26.5 Ma as evidenced by both of onboard and shore-based paleomagnetic data, and this is corresponded to the earliest period of LOW. The sediment profile can be divided into three Units (Unit 1, 2 & 3) based on the changes in both of total number and test size of Oridorsalis umbonatus as well as grain size data of clastic sediments. Unit 2 represents largest values in these three data. Because the total number, test size of O. umbonatus and grain size can be proxy records on the oxygen concentration and circulation intensity of deep water, we interpreted that Unit 2 had been deposited during the period of relatively strengthened NADW. Previous Cibicidoides spp. stable isotope results from the low latitude region of the North Atlantic also support our interpretation that is the intensified formation of NADW during the identical period. In conclusion, our results present a new evidence for the previous ideas that the causes on LOW are directly related to the changes in NADW.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.249-263
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• 2023

Collaborative Filtering, a representative recommendation system methodology, consists of two approaches: neighbor methods and latent factor models. Among these, the latent factor model using matrix factorization decomposes the user-item interaction matrix into two lower-dimensional rectangular matrices, predicting the item's rating through the product of these matrices. Due to the factor vectors inferred from rating patterns capturing user and item characteristics, this method is superior in scalability, accuracy, and flexibility compared to neighbor-based methods. However, it has a fundamental drawback: the need to reflect the diversity of preferences of different individuals for items with no ratings. This limitation leads to repetitive and inaccurate recommendations. The Adaptive Deep Latent Factor Model (ADLFM) was developed to address this issue. This model adaptively learns the preferences for each item by using the item description, which provides a detailed summary and explanation of the item. ADLFM takes in item description as input, calculates latent vectors of the user and item, and presents a method that can reflect personal diversity using an attention score. However, due to the requirement of a dataset that includes item descriptions, the domain that can apply ADLFM is limited, resulting in generalization limitations. This study proposes a Generalized Adaptive Deep Latent Factor Recommendation Model, G-ADLFRM, to improve the limitations of ADLFM. Firstly, we use item ID, commonly used in recommendation systems, as input instead of the item description. Additionally, we apply improved deep learning model structures such as Self-Attention, Multi-head Attention, and Multi-Conv1D. We conducted experiments on various datasets with input and model structure changes. The results showed that when only the input was changed, MAE increased slightly compared to ADLFM due to accompanying information loss, resulting in decreased recommendation performance. However, the average learning speed per epoch significantly improved as the amount of information to be processed decreased. When both the input and the model structure were changed, the best-performing Multi-Conv1d structure showed similar performance to ADLFM, sufficiently counteracting the information loss caused by the input change. We conclude that G-ADLFRM is a new, lightweight, and generalizable model that maintains the performance of the existing ADLFM while enabling fast learning and inference.